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Automatic Hepatic Vessel Segmentation Using Graphics Hardware

机译:使用图形硬件的自动肝血管分割

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The accurate segmentation of liver vessels is an important prerequisite for creating oncologic surgery planning tools as well as medical visualization applications. In this paper, a fully automatic approach is presented to quickly enhance and extract the vascular system of the liver from CT datasets. Our framework consists of three basic modules: vessel enhancement on the graphics processing unit (GPU), automatic vessel segmentation in the enhanced images and an option to verify and refine the obtained results. Tests on 20 clinical datasets of varying contrast quality and acquisition phase were carried out to evaluate the robustness of the automatic segmentation. In addition the presented GPU based method was tested against a CPU implementation to demonstrate the performance gain of using modern graphics hardware. Automatic segmentation using graphics hardware allows reliable and fast extraction of the hepatic vascular system and therefore has the potential to save time for oncologic surgery planning.
机译:肝血管的精确分割是创建肿瘤外科手术规划工具以及医学可视化应用程序的重要前提。在本文中,提出了一种全自动方法,可以从CT数据集中快速增强和提取肝脏的血管系统。我们的框架包含三个基本模块:图形处理单元(GPU)上的血管增强,增强图像中的血管自动分割,以及用于验证和优化所获得结果的选项。对20种不同对比质量和采集阶段的临床数据集进行了测试,以评估自动分割的鲁棒性。此外,还针对CPU实现对基于GPU的方法进行了测试,以证明使用现代图形硬件的性能提升。使用图形硬件的自动分割可以可靠,快速地提取肝血管系统,因此有可能节省肿瘤外科手术计划的时间。

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